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Re: st: Standard error correction when using control function approach to endogeneity

From   Austin Nichols <>
Subject   Re: st: Standard error correction when using control function approach to endogeneity
Date   Tue, 18 Jun 2013 14:27:22 -0400

Johannes Muck <>:

1) yes, just run these to get the same answers:
ivreg y1 x1 x2 (y2 = z1 z2)
ivregress 2sls y1 x1 x2 (y2 = z1 z2)
ssc inst ivreg2
ivreg2 y1 x1 x2 (y2 = z1 z2)

2) yes, you can bootstrap the whole thing, but why would you?

On Tue, Jun 18, 2013 at 11:31 AM, Johannes Muck
<> wrote:
> Dear all,
> I am trying to fit a linear regression model with one endogenous variable
> using the control function approach (two stage residual inclusion estimator)
> as described in Wooldridge (2010, pp. 126-129).
> More specifically, I estimate something like:
> (1)  reg y2 x1 x2 z1 z2
> (2)  predict uhat, res
> (3)  reg y1 y2 x1 x2 uhat
> where y1 is my dependent variable of interest, y2 is the endogenous
> variable, x1 and x2 are exogenous explanatory variables, and z1 and z2 are
> valid instruments for y2.
> Since the fitted residual from the first stage is included in the second
> stage regression as an additional regressor, the standard errors need be to
> corrected. Wooldridge (2010, pp. 157-160) derives the formula for the
> corrected standard errors in his book in Appendix 6A, equation (6.58).
> Now my two questions are:
> (1) Has someone already implemented this standard error correction in Stata
> or do I have to calculate equation (6.58) in Appendix 6A manually?
> (2) Could I also obtain a "standard error correction" by bootstrapping
> equations (1)-(3)?
> Any help is greatly appreciated.
> Best,
> Johannes Muck
> References:
> Wooldridge, J. M. (2010), Econometric Analysis of Cross Section and Panel
> Data, 2nd edition, MIT Press, Cambridge MA.
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